Ouster, a manufacturer of high-resolution LiDAR sensors, announced a partnership with data labeling companies Playment and Scale.AI to rapidly accelerate the implementation of deep learning models in self-driving vehicles and other real-time robotics by developing accurate, multi-layer labeled training data. The companies expect the faster development enabled by the partnership to help put safer autonomous vehicles on the road sooner.
At the core of the partnership is Ouster's OS-1 LiDAR sensor. Ouster's multi-beam flash LiDAR technology outputs intensity, range, and ambient images where every 2D pixel corresponds to a 3D point, which allows its data labeling partners to easily translate between 2D and 3D point clouds.
The teams have worked together for months to establish a common data format and labeling process that combines the image-like output from Ouster's LiDAR sensors and Playment and Scale.AI's labeling toolchains to save perception teams both time and money. According to the companies, the approach removes some of the most difficult and time-consuming aspects of data labeling for companies working on everything from autonomous vehicles to industrial robotics and drones.
They say that the initial result of the partnership is a simplification in the process required to feed LiDAR data through the data annotation APIs provided by Playment and Scale.AI, and the companies are promising to reduce the cost of data labeling by up to 50%.
The partnership has a number of specific advantages for customers, according to the companies. One of them is 10-50% lower cost and faster labeling. Ouster's sensors output data in a 2D camera-like format that allows it to be labeled with a process that builds on the camera labeling tool chain. Another advantage is streamlined data transfer. A standardized, efficient data format reduces the amount of data and associated transfer costs by up to 97%. In addition, no sensor fusion is required because Ouster's LiDAR sensor outputs 2D camera-like imagery in addition to 3D data, eliminating the need to fuse LiDAR and camera outputs to generate synchronous 2D and 3D data. A further benefit is that the system performs automatic 2D mask generation. Customers can now feed a single image to Playment or Scale.AI and receive both 2D instance and semantic segmentation masks and 3D bounding boxes.
"We've been working with Playment and Scale.AI for many months now, and it's deeply satisfying to go public with this partnership knowing our customers will benefit so much from our efforts. Both Playment and Scale.AI are on the cutting edge of data labeling technology, and they've reimagined their LiDAR toolchains around our senor's unique 2D-3D technology to improve accuracy, reduce costs, and eliminate friction. Together with our partners, we're revolutionizing the hardware, software, and services that turn 3D data into actionable inference, with the goal of democratizing access to LiDAR technology," said Ouster CEO Angus Pacala.
Playment Cofounder Ajinkya Malasane said, "We're excited about what this technology means for our customers and our business. We think that this partnership will accelerate the timeline toward safer, more reliable, and more fully autonomous vehicles on the road. We can do so much more when we align our efforts with LiDAR leaders like Ouster."
"Whether they are creating models for autonomous vehicles, drones, robots, or retail stores, our customers get a huge benefit from higher resolution, more accurate data," said Scale.AI CEO Alexandr Wang. "Our partnership with Ouster helps us deliver better data to our customers more quickly."